A graphic designer charges an hourly rate. In July, the only expense is for advertising. The function graphed models the designe
r's net income, y, for July for x hours of work.
Select True or False to describe each statement.
I guessed on this question, but I'm not 100% sure. Please help!
Select True or False to describe each statement.
I guessed on this question, but I'm not 100% sure. Please help!
2 answers:
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Answer:
y = x/4 -1/2
Step-by-step explanation:
given coordinates : ( -2, -1 ) and ( 2 , 0 )
gradient = y2 - y1 / x2 - x1
= 0 - -1 / 2 - -2
= 1/4
equation of line:
y - y1 = m( x - x1 )
y - 0 = 1/4 ( x - 2 )
y = x/4 -1/2
the line shown below to confirm:
Answer:
a) What is the probability that the duration of a particular rainfall event at this location is at least 2 hours?
We want this probability"
At most 3 hours?
b) What is the probability that rainfall duration exceeds the mean value by more than 2 standard deviations?
What is the probability that it is less than the mean value by more than one standard deviation?
Step-by-step explanation:
Previous concepts
The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution". The probability density function is given by:
The cumulative distribution for this function is given by:
We know the value for the mean on this case we have that :
Solution to the problem
Part a
What is the probability that the duration of a particular rainfall event at this location is at least 2 hours?
We want this probability"
At most 3 hours?
Part b
What is the probability that rainfall duration exceeds the mean value by more than 2 standard deviations?
The variance for the esponential distribution is given by:
And the deviation would be:
And the mean is given by
Two deviations correspond to 5.540, so we want this probability:
What is the probability that it is less than the mean value by more than one standard deviation?
For this case we want this probablity: